UNASSIGNED: Unmanned aerial vehicles (UAVs) are widely used in various computer vision applications, especially in intelligent traffic monitoring, as they are agile and simplify operations while boosting efficiency. However, automating these procedures is still a significant challenge due to the difficulty of extracting foreground (vehicle) information from complex traffic scenes.
UNASSIGNED: This paper presents a unique method for autonomous vehicle surveillance that uses FCM to segment aerial images. YOLOv8, which is known for its ability to detect tiny objects, is then used to detect vehicles. Additionally, a system that utilizes ORB features is employed to support vehicle recognition, assignment, and recovery across picture frames. Vehicle tracking is accomplished using DeepSORT, which elegantly combines Kalman filtering with deep learning to achieve precise results.
UNASSIGNED: Our proposed model demonstrates remarkable performance in vehicle identification and tracking with precision of 0.86 and 0.84 on the VEDAI and SRTID datasets, respectively, for vehicle detection.
UNASSIGNED: For vehicle tracking, the model achieves accuracies of 0.89 and 0.85 on the VEDAI and SRTID datasets, respectively.

To achieve Level 4 and above autonomous driving, a robust and stable autonomous driving system is essential to adapt to various environmental changes. This paper aims to perform vehicle pose estimation, a crucial element in forming autonomous driving systems, more universally and robustly. The prevalent method for vehicle pose estimation in autonomous driving systems relies on Real-Time Kinematic (RTK) sensor data, ensuring accurate location acquisition. However, due to the characteristics of RTK sensors, precise positioning is challenging or impossible in indoor spaces or areas with signal interference, leading to inaccurate pose estimation and hindering autonomous driving in such scenarios. This paper proposes a method to overcome these challenges by leveraging objects registered in a high-precision map. The proposed approach involves creating a semantic high-definition (HD) map with added objects, forming object-centric features, recognizing locations using these features, and accurately estimating the vehicle\'s pose from the recognized location. This proposed method enhances the precision of vehicle pose estimation in environments where acquiring RTK sensor data is challenging, enabling more robust and stable autonomous driving. The paper demonstrates the proposed method\'s effectiveness through simulation and real-world experiments, showcasing its capability for more precise pose estimation.

Infusion of 17β-estradiol (E2) into the dorsal hippocampus (DH) of ovariectomized (OVX) mice enhances memory consolidation, an effect that depends on rapid phosphorylation of extracellular signal-regulated kinase (ERK) and Akt. Astrocytic glutamate transporter 1 (GLT-1) modulates neurotransmission via glutamate uptake from the synaptic cleft. However, little is known about the contribution of DH astrocytes, and astrocytic glutamate transport, to the memory-enhancing effects of E2. This study was designed to test whether DH astrocytes contribute to estrogenic modulation of memory consolidation by determining the extent to which DH GLT-1 is necessary for E2 to enhance memory in object recognition and object placement tasks and trigger rapid phosphorylation events in DH astrocytes. OVX female mice were bilaterally cannulated into the DH or the DH and dorsal third ventricle (ICV). Post-training DH infusion of the GLT-1 inhibitor dihydrokainic acid (DHK) dose-dependently impaired memory consolidation in both tasks. Moreover, the memory-enhancing effects of ICV-infused E2 in each task were blocked by DH DHK infusion. E2 increased p42 ERK and Akt phosphorylation in DH astrocytes, and these effects were blocked by DHK. Results suggest the necessity of DH GLT-1 activity for object and spatial memory consolidation, and for E2 to enhance consolidation of these memories and to rapidly activate cell signaling in DH astrocytes. Findings indicate that astrocytic function in the DH of OVX females is necessary for memory formation and is regulated by E2, and suggest an essential role for DH astrocytic GLT-1 activity in the memory-enhancing effects of E2.

Looking leads gaze to objects; seeing recognizes them. Visual crowding makes seeing difficult or impossible before looking brings objects to the fovea. Looking before seeing can be guided by saliency mechanisms in the primary visual cortex (V1). We have proposed that looking and seeing are mainly supported by peripheral and central vision, respectively. This proposal is tested in an observer with central vision loss due to macular degeneration, using a visual search task that can be accomplished solely through looking, but is actually impeded through seeing. The search target is an uniquely oriented, salient, bar among identically shaped bars. Each bar, including the target, is part of an \" \" X \" shape. The target\'s \" X is identical to, although rotated from, the other \" X \'s in the image, which normally causes confusion. However, this observer exhibits no such confusion, presumably because she cannot see the \" X \'s shape, but can look towards the target. This result demonstrates a critical dichotomy between central and peripheral vision.

Acetylation of histone proteins by histone acetyltransferases (HATs), and the resultant change in gene expression, is a well-established mechanism necessary for long-term memory (LTM) consolidation, which is not required for short-term memory (STM). However, we previously demonstrated that the HAT p300/CBP-associated factor (PCAF) also influences hippocampus (HPC)-dependent STM in male rats. In addition to their epigenetic activity, HATs acetylate nonhistone proteins involved in nongenomic cellular processes, such as estrogen receptors (ERs). Given that ERs have rapid, nongenomic effects on HPC-dependent STM, we investigated the potential interaction between ERs and PCAF for STM mediated by the dorsal hippocampus (dHPC). Using a series of pharmacological agents administered directly into the dHPC, we reveal a functional interaction between PCAF and ERα in the facilitation of short-term object-in-place memory in male but not female rats. This interaction was specific to ERα, while ERβ agonism did not enhance STM. It was further specific to dHPC STM, as the effect was not present in the dHPC for LTM or in the perirhinal cortex. Further, while STM required local (i.e., dHPC) estrogen synthesis, the facilitatory interaction effect appeared independent of estrogens. Finally, western blot analyses demonstrated that PCAF activation in the dHPC rapidly (5 min) activated downstream estrogen-related cell signaling kinases (c-Jun N-terminal kinase and extracellular signal-related kinase). Collectively, these findings indicate that PCAF, which is typically implicated in LTM through epigenetic processes, also influences STM in the dHPC, possibly via nongenomic ER activity. Critically, this novel PCAF-ER interaction might exist as a male-specific mechanism supporting STM.

暂无摘要。

UNASSIGNED: Alzheimer\'s disease (AD) is a neurodegenerative disease specified by chronic and irreversible destruction of neurons. This study aimed to evaluate the effects of different extracts (aqueous, hydroalcoholic, hexane, and ethyl acetate) and manna of Echinops cephalotes (EC) on impaired cognitive function induced by scopolamine in mice. EC is shown to have anti-cholinesterase-butyrylcholinesterase activities.
UNASSIGNED: In this study, aqueous and hydroalcoholic extracts, hexane and ethyl acetate fractions of EC (25, 50, 100 mg/kg, i.p.), and the manna (25, 50, 100 mg/kg, gavage) were administered for 14 days alongside scopolamine (0.7 mg/kg, i.p.). Rivastigmine (reference drug) was administered for 2 weeks i.p. Mice were tested for their memory function using two behavioral models, object recognition test (ORT) and passive avoidance test (PAT).
UNASSIGNED: Administration of scopolamine significantly impaired memory function in both behavioral models. In the PAT model, all extracts at 50 and 100 mg/kg significantly reversed the effect of memory destruction caused by scopolamine. At a lower dose of 25 mg/kg, however, none of the extracts were able to significantly change the step-through latency time. In the ORT model, however, administration of all extracts at 50 and 100 mg/kg, significantly increased the recognition index. Only the manna and the aqueous extract at 25 mg/kg were able to reverse scopolamine-induced memory impairment.
UNASSIGNED: These results suggest that all forms of EC extracts improve memory impairment induced by scopolamine comparably to rivastigmine. Whether the effects are sustained over a longer period remains to be tested in future work.

Previous studies showed that elongation and symmetry (two ubiquitous aspects of natural stimuli) are important attributes in object perception and recognition, which in turn suggests that these geometrical factors may contribute to the selection of perceptual reference-frames. However, whether and how these attributes guide the selection of reference-frames is still poorly understood. The goal of this study was to examine systematically the roles of elongation and symmetry, as well as their combination, in the selection of reference axis and how these axes are developed for unfamiliar objects. We designed our experiments to eliminate two potential confounding factors: (i) extraneous environmental cues, such as edges of the screen, etc. (by using VR) and (ii) pre-learned cues for familiar objects and shapes (by using reinforcement learning of novel shapes). We used algorithmically generated textures with different orientations having specified levels of symmetry and elongation as the stimuli. In each trial, we presented only one stimulus and asked observers to report if the stimulus was in its original form or a flipped (mirror-image) one. Feedback was provided at the end of each trial. Based on previous studies on mental rotation, we hypothesized that the selection of a reference-frame defined by symmetry and/or elongation would be revealed by a linear relationship between reaction-times and the angular-deviation from either the most symmetrical or the most elongated orientation. Our results are consistent with this hypothesis. We found that subjects performed mental rotation to transform images to their reference axes and used the most symmetrical or elongated orientation as the reference axis when only one factor was presented, and they used a \"winner-take-all\" strategy when both factors were presented, with elongation being more dominant than symmetry. We discuss theoretical implications of these findings, in particular in the context of \"canonical sensorimotor theory.\"

People differ in how well they search. What are the factors that might contribute to this variability? We tested the contribution of two cognitive abilities: visual working memory (VWM) capacity and object recognition ability. Participants completed three tasks: a difficult inefficient visual search task, where they searched for a target letter T among skewed L distractors; a VWM task, where they memorized a color array and then identified whether a probed color belonged to the previous array; and the Novel Object Memory Test (NOMT), where they learnt complex novel objects and then identified them amongst objects that closely resembled them. Exploratory and confirmatory factor analyses revealed that there are two latent factors that explain the shared variance among these three tasks: a factor indicative of the level of caution participants exercised during the challenging visual search task, and a factor representing their visual cognitive abilities. People who score high on the search cautiousness tend to perform a more accurate but slower search. People who score high on the visual cognitive ability factor tend to have a higher VWM capacity, a better object recognition ability, and a faster search speed. The results reflect two points: (1) Visual search tasks share components with visual working memory and object recognition tasks. (2) Search performance is influenced not only by the search display\'s properties but also by individual predispositions such as caution and general visual abilities. This study introduces new factors for consideration when interpreting variations in visual search behaviors.

Object classification has been proposed as a principal objective of the primate ventral visual stream and has been used as an optimization target for deep neural network models (DNNs) of the visual system. However, visual brain areas represent many different types of information, and optimizing for classification of object identity alone does not constrain how other information may be encoded in visual representations. Information about different scene parameters may be discarded altogether (\'invariance\'), represented in non-interfering subspaces of population activity (\'factorization\') or encoded in an entangled fashion. In this work, we provide evidence that factorization is a normative principle of biological visual representations. In the monkey ventral visual hierarchy, we found that factorization of object pose and background information from object identity increased in higher-level regions and strongly contributed to improving object identity decoding performance. We then conducted a large-scale analysis of factorization of individual scene parameters - lighting, background, camera viewpoint, and object pose - in a diverse library of DNN models of the visual system. Models which best matched neural, fMRI, and behavioral data from both monkeys and humans across 12 datasets tended to be those which factorized scene parameters most strongly. Notably, invariance to these parameters was not as consistently associated with matches to neural and behavioral data, suggesting that maintaining non-class information in factorized activity subspaces is often preferred to dropping it altogether. Thus, we propose that factorization of visual scene information is a widely used strategy in brains and DNN models thereof.
When looking at a picture, we can quickly identify a recognizable object, such as an apple, applying a single word label to it. Although extensive neuroscience research has focused on how human and monkey brains achieve this recognition, our understanding of how the brain and brain-like computer models interpret other complex aspects of a visual scene – such as object position and environmental context – remains incomplete. In particular, it was not clear to what extent object recognition comes at the expense of other important scene details. For example, various aspects of the scene might be processed simultaneously. On the other hand, general object recognition may interfere with processing of such details. To investigate this, Lindsey and Issa analyzed 12 monkey and human brain datasets, as well as numerous computer models, to explore how different aspects of a scene are encoded in neurons and how these aspects are represented by computational models. The analysis revealed that preventing effective separation and retention of information about object pose and environmental context worsened object identification in monkey cortex neurons. In addition, the computer models that were the most brain-like could independently preserve the other scene details without interfering with object identification. The findings suggest that human and monkey high level ventral visual processing systems are capable of representing the environment in a more complex way than previously appreciated. In the future, studying more brain activity data could help to identify how rich the encoded information is and how it might support other functions like spatial navigation. This knowledge could help to build computational models that process the information in the same way, potentially improving their understanding of real-world scenes.